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BackgroundIncreasing physical activity (PA) is an effective strategy to slow reductions in cortical volume and maintain cognitive function in older adulthood. However, PA does not exist in isolation, but coexists with sleep and sedentary behaviour to make up the 24-hour day. We investigated how the balance of all three behaviours (24-hour time-use composition) is associated with grey matter volume in healthy older adults, and whether grey matter volume influences the relationship between 24-hour time-use composition and cognitive function.MethodsThis cross-sectional study included 378 older adults (65.6 ± 3.0 years old, 123 male) from the ACTIVate study across two Australian sites (Adelaide and Newcastle). Time-use composition was captured using 7-day accelerometry, and T1-weighted magnetic resonance imaging was used to measure grey matter volume both globally and across regions of interest (ROI: frontal lobe, temporal lobe, hippocampi, and lateral ventricles). Pairwise correlations were used to explore univariate associations between time-use variables, grey matter volumes and cognitive outcomes. Compositional data analysis linear regression models were used to quantify associations between ROI volumes and time-use composition, and explore potential associations between the interaction between ROI volumes and time-use composition with cognitive outcomes.ResultsAfter adjusting for covariates (age, sex, education), there were no significant associations between time-use composition and any volumetric outcomes. There were significant interactions between time-use composition and frontal lobe volume for long-term memory (p=0.018) and executive function (p=0.018), and between time-use composition and total grey matter volume for executive function (p=0.028). Spending more time in moderate-vigorous PA was associated with better long-term memory scores, but only for those with smaller frontal lobe volume (below the sample mean). Conversely, spending more time in sleep and less time in sedentary behaviour was associated with better executive function in those with smaller total grey matter volume.ConclusionsAlthough 24-hour time use was not associated with total or regional grey matter independently, total grey matter and frontal lobe grey matter volume mediated the relationship between time-use composition and several cognitive outcomes. Future studies should investigate these relationships longitudinally to assess whether changes in time-use composition correspond to changes in grey matter volume and cognition.

BackgroundIn Alzheimer’s disease, plasma Aβ1-42 and p-tau predict high amyloid status from Aβ-PET, however the extent to which combination of both plasma assays predict remains unknown.MethodsPrototype Simoa assays were used to measure plasma samples from cognitively normal (CN) and symptomatic adults in the Australian Imaging, Biomarkers and Lifestyle (AIBL) study.ResultsThe p-tau181/Aβ1-42 ratio showed the best prediction of Aβ-PET across all participants (AUC=0.905, 95%CI:0.86-0.95) and in CN (AUC=0.873; 0.80–0.94), and symptomatic (AUC=0.908; 0.82–1.00) adults. Plasma p-tau181/Aβ1-42 ratio correlated with CSF-p-tau181 (Elecsys®, Spearman’s ρ=0.74, P1-42 ratio also predicted future rates of cognitive decline assessed by AIBL PACC or CDR-SOB (PDiscussionPlasma p-tau181/Aβ1-42 ratio predicted both Aβ-PET status and cognitive decline, demonstrating potential as both a diagnostic aid and as a screening and prognostic assay for preclinical Alzheimer’s disease trials.

Background Tau PET imaging enables prospective longitudinal observation of the rate and location of tau accumulation in Alzheimer's disease (AD). 18F-MK6240 is a newer, high affinity tracer for the paired helical filaments of tau in AD. It is widely used in clinical trials, despite sparse longitudinal natural history data. We aimed to evaluate the impact of disease stage, and two reference regions on the magnitude and effect size of regional change. Methods One hundred and fifty-eight participants: 83 cognitively unimpaired (CU) Aβ-, 37 CU Aβ+, 19 mild cognitively impaired (MCI) Aβ+ and 19 AD Aβ+ had annual 18F-MK6240 PET for one or two years (mean 1.6 years). Standardized uptake value ratios (SUVR) were generated for three in-house composite ROI: mesial temporal (Me), temporoparietal (Te), and rest of neocortex (R), and a Free-Surfer derived meta-temporal (MT) ROI. Two reference regions were examined: cerebellar cortex (SUVRCb) and eroded subcortical white matter (SUVRWM). Results Low rates of accumulation were seen in CU Aβ-, predominantly in the mesial temporal lobe (MTL). In CU Aβ+, increase was greatest in the MTL, particularly the amygdala. In MCI Aβ+, a similar increase was seen in MTL, but also globally in the cortex. In AD Aβ+, greatest increase was in temporoparietal and frontal regions, with a decrease in the MTL. In CU and MCI increases were greater using SUVRWM. In AD, the SUVRCb showed marginally greater increase. Interpolation of the data suggests it takes approximately two decades to accumulate tau to the typical levels found in AD, similar to the rates of accumulation of Aβ plaques. Conclusions The rate of tau accumulation varies according to brain region and baseline disease stage, confirming previous reports. The PET measured change is greater, with fewer outliers, using an eroded white matter reference region, except in AD. While the eroded subcortical white matter reference may be preferred for trials in preclinical AD, the cerebellar cortex would be preferred for trials in symptomatic AD.

INTRODUCTIONWe evaluated a new Simoa plasma assay for phosphorylated tau at aa217 enhanced by additional ptau sites (p217+tau).METHODSPlasma p217+tau levels were compared to 18F-NAV4694 amyloid-beta (Aβ) PET and 18F-MK6240 tau PET in 174 cognitively impaired (CI) and 223 cognitively unimpaired (CU) participants.RESULTSCompared to Aβ-CU, the plasma levels of p217+tau increased two-fold in Aβ+ CU and 3.5-fold in Aβ+ CI. In Aβ-the p217+tau levels did not significantly differ between CU, MCI or dementia. P217+tau correlated with Aβ centiloids ρ=0.67 (CI 0.64; CU 0.45) and tau SUVRMT ρ=0.63 (CI 0.69; CU 0.34). Area under curve (AUC) for AD vs Aβ-CU was 0.94, for AD vs other dementia was 0.93, for Aβ+ vs Aβ– PET was 0.89 and for tau+ vs tau-PET was 0.89.DISCUSSIONPlasma p217+tau levels elevate early in the AD continuum and correlate well with Aβ and tau PET.Research in ContextSystematic review: The authors reviewed the literature using PubMed, meeting abstracts and presentations. Plasma phospho-tau measures compare well to PET and post-mortem across the continuum of AD but accuracy varies across ptau target sites and assay methods. There are no reports comparing PET to plasma assays targeting multiple sites of tau phosphorylation as typically found in AD. The p217+tau assay targets p217 with binding enhanced by phosphorylation at additional sites such as aa212.Interpretation: Plasma p217+tau elevates early and correlates with both Aβ and tau as measured by PET indicating that tau phosphorylation is an early event in AD and occurs with Aβ deposition. Plasma p217+tau measurement should assist both selection for trials and diagnosis of AD.Future directions: Further validation studies, head-to-head comparison to other assays, assessing the influence of co-morbidities and the ability to measure change in brain Aβ and tau levels are required.

BackgroundOngoing research seeks to identify blood-based biomarkers able to predict the onset and progression of Alzheimer’s disease (AD). A potential biomarker is the unfolded conformational variant of p53, previously observed in individuals in the prodromal and clinical AD stages. In this retrospective study, we compare diagnostic and prognostic performances of measures of the amyloid β load with those of a conformational variant of U-p53 in plasma samples from individuals participating in the Australian Imaging, Biomarkers and Lifestyle (AIBL) cohort.MethodsImmunoprecipitation (IP) followed by liquid chromatography (LC) tandem mass spectrometry (MS/MS) and protein sequencing in plasma samples from the AIBL study identified the clinically relevant AZ 284®peptide, representing a measure of the U-p53 conformational variant (U-p53AZ). Based on U-p53AZquantification via IP/LC electrospray ionisation-coupled MS/MS (AlzoSure®Predict test) on 515 samples from 482 individuals from the AIBL cohort, the predictive performance of U-p53AZwas assessed and compared with amyloid load as measured by amyloid β-positron emission tomography (Aβ-PET). Its predictive performance was determined at 36, 54, 72 and 90 months following baseline assessment.ResultsU-p53AZwas able to identify individuals with AD dementia with an area under the receiver operating characteristic curve (AUC) of 99%. U-p53AZoutperformed the conventional Aβ-PET measures in predicting the onset of AD dementia both from preclinical (AUC=98%) and prodromal stages (AUC=89%), even 90 months prior to onset (AUC=99%). Additionally, the estimated predictive performance of U-p53AZwas superior (AUC ≥98%) to other risk factors (i.e., gender, Aβ-PET andAPOEε4 allele status) in identifying individuals at high risk for progression to AD.ConclusionThese findings support use of U-p53AZas blood-based biomarker predicting if individuals, at both asymptomatic and MCI stages, would progress to AD at least six years prior to the onset of clinical AD dementia.

1AbstractMagnetic Resonance Imaging (MRI) motion artefacts frequently complicate structural and diffusion MRI analyses. While diffusion imaging is easily ‘scrubbed’ of motion affected volumes, the same is not true for structural images. Structural images are critical to most diffusion-imaging pipelines thus their corruption can lead to disproportionate data loss. To enable diffusion-image processing when structural images have been corrupted, we propose a means by which synthetic structural images can be generated from diffusion MRI. This technique combines multi-tissue constrained spherical deconvolution, which is central to many existing diffusion analyses, with the Bloch equations which allow simulation of MRI intensities given scanner parameters and magnetic resonance (MR) tissue properties. We applied this technique to 32 scans, including those acquired on different scanners, with different protocols and with pathology present. The resulting synthetic T1w and T2w images were visually convincing and exhibited similar tissue contrast to acquired structural images. These were also of sufficient quality to drive a Freesurfer-based tractographic analysis. In this analysis, probabilistic tractography connecting the thalamus to the primary sensorimotor cortex was delineated with Freesurfer, using either real or synthetic structural images. Tractography for real and synthetic conditions was largely identical in terms of both voxels encountered (Dice 0.88 – 0.95) and mean fractional anisotropy (intrasubject absolute difference 0.00 – 0.02). We provide executables for the proposed technique in the hope that these may aid the community in analysing datasets where structural image corruption is common, such as studies of children or cognitively impaired persons.HighlightsWe propose a simple means of synthesizing T1w and T2w images from diffusion dataThe proposed method worked well for a variety of acquisitionsSynthetic images showed tissue contrast akin to acquired imagesSynthetic images were high enough quality to be used for Freesurfer seeded diffusion tractographyThis method enables analysis of datasets where motion has corrupted acquired structural MRIs

1AbstractQuadrantanopia caused by inadvertent severing of Meyer’s Loop of the optic radiation is a well-recognised complication of temporal lobectomy for conditions such as epilepsy. Dissection studies indicate that the anterior extent of Meyer’s Loop varies considerably between individuals. Quantifying this for individual patients is thus an important step to improve the safety profile of temporal lobectomies. Previous attempts to delineate Meyer’s Loop using diffusion MRI tractography have had difficulty estimating its full anterior extent, required manual ROI placement, and/or relied on advanced diffusion sequences that cannot be acquired routinely in most clinics. Here we present CONSULT – a pipeline that can delineate the optic radiation from raw DICOM data in a completely automated way via a combination of robust preprocessing, segmentation, and alignment stages, plus simple improvements that bolster the efficiency and reliability of standard tractography. We tested CONSULT on 694 scans of predominantly healthy participants (538 unique brains), including both advanced acquisitions and simpler acquisitions that could be acquired in clinically acceptable timeframes. Delineations completed without error in 99.4% of the scans. The distance between Meyer’s Loop and the temporal pole closely matched both averages and ranges reported in dissection studies for all tested sequences. Median scan-rescan error of this distance was 1mm. When tested on two participants with considerable pathology, delineations were successful and realistic. Through this, we demonstrate not only how to identify Meyer’s Loop with clinically accessible sequences, but also that this can be achieved without fundamental changes to tractography algorithms or complex post-processing methods.HighlightsWe propose a fully automated means of delineating the optic radiation using diffusion MRI from DICOM dataAnatomical measurements from tractography of over 500 brains align well with previous dissection studiesThe proposed pipeline works well with clinically accessible and advanced acquisitionsMedian scan-rescan error was 1mmPlausible tractography was generated when pathology was present

This prospective cohort study, “Prospective Imaging Study of Ageing: Genes, Brain and Behaviour” (PISA) seeks to characterise the phenotype and natural history of healthy adult Australians at high future risk of Alzheimer’s disease (AD). In particular, we are recruiting mid-life Australians with high and low genetic risk of dementia to discover biological markers of early neuropathology, identify modifiable risk factors, and establish the very earliest phenotypic and neuronal signs of disease onset. PISA utilises genetic prediction to recruit and enrich a prospective cohort and follow them longitudinally. Online surveys and cognitive testing are used to characterise an Australia-wide sample currently totalling nearly 3,000 participants. Participants from a defined at-risk cohort and positive controls (clinical cohort of patients with mild cognitive impairment or early AD) are invited for onsite visits for lifestyle monitoring, detailed neurocognitive testing, blood sample donation, plus functional, structural and molecular neuroimaging. This paper describes recruitment of the PISA cohort, study methodology and baseline demographics.Author ApprovalAll authors have seen and approved this manuscript.

Participant movement can deleteriously affect MR image quality. Further, for the visualization and segmentation of small anatomical structures, there is a need to improve image quality, specifically signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), by acquiring multiple anatomical scans consecutively. We aimed to ameliorate movement artefacts and increase SNR in a high-resolution turbo spin-echo (TSE) sequence acquired thrice using non-linear realignment in order to improve segmentation consistency of the hippocampus subfields. We assessed the method in young healthy participants, Motor Neurone Disease patients, and age matched controls. Results show improved image segmentation of the hippocampus subfields when comparing template-based segmentations with individual segmentations with Dice overlaps N=51;ps< 0.001 (Friedman’s test) and higher sharpnessps< 0.001 in non-linearly realigned scans as compared to linearly, and arithmetically averaged scans.